Sophia M. Adelson

The paper examines motivations and outcomes of elective genomic sequencing across research, clinical, and commercial contexts, finding most participants found results medically important but few shared them with healthcare providers.

The paper develops a machine learning model to prioritize genes for newborn sequencing programs based on factors like evidence of disease natural history and treatment efficacy.

This paper proposes a fetal actionable findings list for genomic sequencing in pregnancy to identify clinically relevant incidental variants.